library(ggplot2)
library(patchwork)
library(dplyr)
library(gridExtra)
library(DT)
library(readxl)
library(cowplot)
library(readr)
library(RColorBrewer)
library(ggrepel)
library(gplots)#
library(pheatmap)
rss <- read.csv("/data/rajewsky/home/skim/Microglia_Heppner/201912_10X_9sets/pyscenic/20220315_pyscenic_preprocessed__rss_cell_type_1st.csv",row.names = 1)
rss_t <- rss %>% t %>% as.data.frame
rss2 <- read.csv("/data/rajewsky/home/skim/Microglia_Heppner/201912_10X_9sets/pyscenic/20220315_pyscenic_preprocessed__rss_cell_type_2nd.csv",row.names = 1)
rss2_t <- rss2 %>% t %>% as.data.frame
rss3 <- read.csv("/data/rajewsky/home/skim/Microglia_Heppner/201912_10X_9sets/pyscenic/20220315_pyscenic_preprocessed__rss_cell_type_3rd.csv",row.names = 1)
rss3_t <- rss3 %>% t %>% as.data.frame
rss4 <- read.csv("/data/rajewsky/home/skim/Microglia_Heppner/201912_10X_9sets/pyscenic/20220315_pyscenic_preprocessed__rss_cell_type_4th.csv",row.names = 1)
rss4_t <- rss4 %>% t %>% as.data.frame
# reg <- read.csv("/data/rajewsky/home/skim/Microglia_Heppner/201912_10X_9sets/pyscenic/reg.csv", stringsAsFactors=FALSE)
# reg[1,1] <- "TF"
# reg[1,2] <- "MotifID"
# colnames(reg) <- reg[1, ]
# reg <- reg[-c(1,2), ]
# reg$AUC <- reg$AUC %>% as.numeric
# reg$NES <- reg$NES %>% as.numeric
# reg$MotifSimilarityQvalue <- reg$MotifSimilarityQvalue %>% as.numeric
# reg$OrthologousIdentity <- reg$OrthologousIdentity %>% as.numeric
# reg$RankAtMax <- reg$RankAtMax %>% as.numeric
# saveRDS(reg, file = "/data/rajewsky/home/skim/Microglia_Heppner/201912_10X_9sets/pyscenic/reg_final.rda")
reg <- readRDS(file = "/data/rajewsky/projects/cdr1as_ko_snRNA/3rd_sequencing_run/pyscenic/reg_final.rda")
1-1. glial cells raw
rss_t_1 <- rss_t[, c("Astrocytes_Ctrl", "Astrocytes_AD", "Astrocytes_ADp40KO",
"Microglia_Ctrl", "Microglia_AD", "Microglia_ADp40KO",
"MOL_Ctrl","MOL_AD","MOL_ADp40KO",
"MFOL_Ctrl","MFOL_AD","MFOL_ADp40KO",
"NFOL_Ctrl","NFOL_AD","NFOL_ADp40KO",
"OPC_Ctrl","OPC_AD","OPC_ADp40KO")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss_t_1), cluster_cols = FALSE)
1-2. glial cells z-score
rss_t_z <- as.data.frame(t(apply(rss_t, 1, function(x) (x - mean(x)) / sd(x))))
rss_t_z <- rss_t_z[, c("Astrocytes_Ctrl", "Astrocytes_AD", "Astrocytes_ADp40KO",
"Microglia_Ctrl", "Microglia_AD", "Microglia_ADp40KO",
"MOL_Ctrl","MOL_AD","MOL_ADp40KO",
"MFOL_Ctrl","MFOL_AD","MFOL_ADp40KO",
"NFOL_Ctrl","NFOL_AD","NFOL_ADp40KO",
"OPC_Ctrl","OPC_AD","OPC_ADp40KO")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss_t_z), cluster_cols = FALSE)
# heatmap.2(as.matrix(rss_t_z),
# trace="none",
# col=rev(morecols(50)),
# #Colv=FALSE,
# main="cell number per cluster in all samples",
# scale="row", lhei=c(1.5, 10), lwid = c(2,10), cexCol=0.8)
1-3. neuronal cells raw
rss_t_1 <- rss_t[, c("subiculum_Ctrl", "subiculum_AD", "subiculum_ADp40KO",
"CA1_Ctrl", "CA1_AD", "CA1_ADp40KO",
"CA2_3_Ctrl","CA2_3_AD","CA2_3_ADp40KO",
"Dentate_Gyrus_Ctrl","Dentate_Gyrus_AD","Dentate_Gyrus_ADp40KO",
"Inhibitory_Neurons_Ctrl","Inhibitory_Neurons_AD","Inhibitory_Neurons_ADp40KO")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss_t_1), cluster_cols = FALSE)
1-4. neuronal cells z-score
rss_t_z <- as.data.frame(t(apply(rss_t, 1, function(x) (x - mean(x)) / sd(x))))
rss_t_z <- rss_t_z[, c("subiculum_Ctrl", "subiculum_AD", "subiculum_ADp40KO",
"CA1_Ctrl", "CA1_AD", "CA1_ADp40KO",
"CA2_3_Ctrl","CA2_3_AD","CA2_3_ADp40KO",
"Dentate_Gyrus_Ctrl","Dentate_Gyrus_AD","Dentate_Gyrus_ADp40KO",
"Inhibitory_Neurons_Ctrl","Inhibitory_Neurons_AD","Inhibitory_Neurons_ADp40KO")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss_t_z), cluster_cols = FALSE)
2-1. glial cells replicates raw
rss2_t_1 <- rss2_t[, c("Astrocytes_Ctrl_1", "Astrocytes_Ctrl_4", "Astrocytes_Ctrl_7",
"Astrocytes_AD_3", "Astrocytes_AD_6","Astrocytes_AD_9",
"Astrocytes_ADp40KO_2","Astrocytes_ADp40KO_5","Astrocytes_ADp40KO_8",
"Microglia_Ctrl_1", "Microglia_Ctrl_4", "Microglia_Ctrl_7",
"Microglia_AD_3", "Microglia_AD_6","Microglia_AD_9",
"Microglia_ADp40KO_2","Microglia_ADp40KO_5","Microglia_ADp40KO_8")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss2_t_1), cluster_cols = FALSE)
2-2. glial cells replicates z-score
rss2_t_z <- as.data.frame(t(apply(rss2_t, 1, function(x) (x - mean(x)) / sd(x))))
rss2_t_z_1 <- rss2_t_z[, c("Astrocytes_Ctrl_1", "Astrocytes_Ctrl_4", "Astrocytes_Ctrl_7",
"Astrocytes_AD_3", "Astrocytes_AD_6","Astrocytes_AD_9",
"Astrocytes_ADp40KO_2","Astrocytes_ADp40KO_5","Astrocytes_ADp40KO_8",
"Microglia_Ctrl_1", "Microglia_Ctrl_4", "Microglia_Ctrl_7",
"Microglia_AD_3", "Microglia_AD_6","Microglia_AD_9",
"Microglia_ADp40KO_2","Microglia_ADp40KO_5","Microglia_ADp40KO_8")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss2_t_z_1), cluster_cols = FALSE)
2-3. Oligo cells replicates raw
rss2_t_1 <- rss2_t[, c("OPC_Ctrl_1", "OPC_Ctrl_4", "OPC_Ctrl_7",
"OPC_AD_3", "OPC_AD_6","OPC_AD_9",
"OPC_ADp40KO_2","OPC_ADp40KO_5","OPC_ADp40KO_8",
"NFOL_Ctrl_1", "NFOL_Ctrl_4", "NFOL_Ctrl_7",
"NFOL_AD_3", "NFOL_AD_6","NFOL_AD_9",
"NFOL_ADp40KO_2","NFOL_ADp40KO_5","NFOL_ADp40KO_8",
"MFOL_Ctrl_1", "MFOL_Ctrl_4", "MFOL_Ctrl_7",
"MFOL_AD_3", "MFOL_AD_6","MFOL_AD_9",
"MFOL_ADp40KO_2","MFOL_ADp40KO_5","MFOL_ADp40KO_8",
"MOL_Ctrl_1", "MOL_Ctrl_4", "MOL_Ctrl_7",
"MOL_AD_3", "MOL_AD_6","MOL_AD_9",
"MOL_ADp40KO_2","MOL_ADp40KO_5","MOL_ADp40KO_8")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss2_t_1), cluster_cols = FALSE)
2-4. Oligo cells replicates z-score
rss2_t_z_1 <- rss2_t_z[, c("OPC_Ctrl_1", "OPC_Ctrl_4", "OPC_Ctrl_7",
"OPC_AD_3", "OPC_AD_6","OPC_AD_9",
"OPC_ADp40KO_2","OPC_ADp40KO_5","OPC_ADp40KO_8",
"NFOL_Ctrl_1", "NFOL_Ctrl_4", "NFOL_Ctrl_7",
"NFOL_AD_3", "NFOL_AD_6","NFOL_AD_9",
"NFOL_ADp40KO_2","NFOL_ADp40KO_5","NFOL_ADp40KO_8",
"MFOL_Ctrl_1", "MFOL_Ctrl_4", "MFOL_Ctrl_7",
"MFOL_AD_3", "MFOL_AD_6","MFOL_AD_9",
"MFOL_ADp40KO_2","MFOL_ADp40KO_5","MFOL_ADp40KO_8",
"MOL_Ctrl_1", "MOL_Ctrl_4", "MOL_Ctrl_7",
"MOL_AD_3", "MOL_AD_6","MOL_AD_9",
"MOL_ADp40KO_2","MOL_ADp40KO_5","MOL_ADp40KO_8")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss2_t_z_1), cluster_cols = FALSE)
2-5. Neuronal cells replicates raw
rss2_t_1 <- rss2_t[, c("subiculum_Ctrl_1", "subiculum_Ctrl_4", "subiculum_Ctrl_7",
"subiculum_AD_3", "subiculum_AD_6","subiculum_AD_9",
"subiculum_ADp40KO_2","subiculum_ADp40KO_5","subiculum_ADp40KO_8",
"Dentate_Gyrus_Ctrl_1", "Dentate_Gyrus_Ctrl_4", "Dentate_Gyrus_Ctrl_7",
"Dentate_Gyrus_AD_3", "Dentate_Gyrus_AD_6","Dentate_Gyrus_AD_9",
"Dentate_Gyrus_ADp40KO_2","Dentate_Gyrus_ADp40KO_5","Dentate_Gyrus_ADp40KO_8",
"CA1_Ctrl_1", "CA1_Ctrl_4", "CA1_Ctrl_7",
"CA1_AD_3", "CA1_AD_6","CA1_AD_9",
"CA1_ADp40KO_2","CA1_ADp40KO_5","CA1_ADp40KO_8",
"CA2_3_Ctrl_1", "CA2_3_Ctrl_4", "CA2_3_Ctrl_7",
"CA2_3_AD_3", "CA2_3_AD_6","CA2_3_AD_9",
"CA2_3_ADp40KO_2","CA2_3_ADp40KO_5","CA2_3_ADp40KO_8",
"Inhibitory_Neurons_Ctrl_1", "Inhibitory_Neurons_Ctrl_4", "Inhibitory_Neurons_Ctrl_7",
"Inhibitory_Neurons_AD_3", "Inhibitory_Neurons_AD_6","Inhibitory_Neurons_AD_9",
"Inhibitory_Neurons_ADp40KO_2","Inhibitory_Neurons_ADp40KO_5","Inhibitory_Neurons_ADp40KO_8")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss2_t_1), cluster_cols = FALSE)
2-6. Neuronal cells replicates z-score
rss2_t_z_1 <- rss2_t_z[, c("subiculum_Ctrl_1", "subiculum_Ctrl_4", "subiculum_Ctrl_7",
"subiculum_AD_3", "subiculum_AD_6","subiculum_AD_9",
"subiculum_ADp40KO_2","subiculum_ADp40KO_5","subiculum_ADp40KO_8",
"Dentate_Gyrus_Ctrl_1", "Dentate_Gyrus_Ctrl_4", "Dentate_Gyrus_Ctrl_7",
"Dentate_Gyrus_AD_3", "Dentate_Gyrus_AD_6","Dentate_Gyrus_AD_9",
"Dentate_Gyrus_ADp40KO_2","Dentate_Gyrus_ADp40KO_5","Dentate_Gyrus_ADp40KO_8",
"CA1_Ctrl_1", "CA1_Ctrl_4", "CA1_Ctrl_7",
"CA1_AD_3", "CA1_AD_6","CA1_AD_9",
"CA1_ADp40KO_2","CA1_ADp40KO_5","CA1_ADp40KO_8",
"CA2_3_Ctrl_1", "CA2_3_Ctrl_4", "CA2_3_Ctrl_7",
"CA2_3_AD_3", "CA2_3_AD_6","CA2_3_AD_9",
"CA2_3_ADp40KO_2","CA2_3_ADp40KO_5","CA2_3_ADp40KO_8",
"Inhibitory_Neurons_Ctrl_1", "Inhibitory_Neurons_Ctrl_4", "Inhibitory_Neurons_Ctrl_7",
"Inhibitory_Neurons_AD_3", "Inhibitory_Neurons_AD_6","Inhibitory_Neurons_AD_9",
"Inhibitory_Neurons_ADp40KO_2","Inhibitory_Neurons_ADp40KO_5","Inhibitory_Neurons_ADp40KO_8")]
mypalette <- brewer.pal(11,"RdYlBu")
morecols <- colorRampPalette(mypalette)
par(mar=c(1,1,1,1))
pheatmap(as.matrix(rss2_t_z_1), cluster_cols = FALSE)
sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-redhat-linux-gnu (64-bit)
## Running under: CentOS Linux 7 (Core)
##
## Matrix products: default
## BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] pheatmap_1.0.12 gplots_3.1.1 ggrepel_0.9.1 RColorBrewer_1.1-2
## [5] readr_2.1.2 cowplot_1.1.1 readxl_1.3.1 DT_0.18
## [9] gridExtra_2.3 dplyr_1.0.7 patchwork_1.1.1 ggplot2_3.3.5
##
## loaded via a namespace (and not attached):
## [1] gtools_3.9.2 tidyselect_1.1.1 xfun_0.29 bslib_0.2.5.1
## [5] purrr_0.3.4 colorspace_2.0-2 vctrs_0.3.8 generics_0.1.1
## [9] htmltools_0.5.2 yaml_2.2.1 utf8_1.2.2 rlang_0.4.12
## [13] jquerylib_0.1.4 pillar_1.6.4 glue_1.6.1 withr_2.4.3
## [17] DBI_1.1.1 lifecycle_1.0.1 stringr_1.4.0 munsell_0.5.0
## [21] gtable_0.3.0 cellranger_1.1.0 caTools_1.18.2 htmlwidgets_1.5.4
## [25] evaluate_0.14 knitr_1.37 tzdb_0.2.0 fastmap_1.1.0
## [29] fansi_1.0.2 highr_0.9 Rcpp_1.0.8 KernSmooth_2.23-15
## [33] scales_1.1.1 jsonlite_1.7.3 hms_1.1.1 digest_0.6.29
## [37] stringi_1.7.6 grid_3.6.0 bitops_1.0-7 tools_3.6.0
## [41] magrittr_2.0.1 sass_0.4.0 tibble_3.1.6 crayon_1.4.2
## [45] pkgconfig_2.0.3 ellipsis_0.3.2 assertthat_0.2.1 rmarkdown_2.11
## [49] R6_2.5.1 compiler_3.6.0